A multi-axial and high-cycle fatigue life prediction model based on critical plane criterion

Yang, Jian; Gong, Yu; Jiang, Linfei; Lin, Wanjia; Líu, Hao

doi:10.1016/j.jmrt.2022.04.069

Cited by 11 publications

(8 citation statements)

References 43 publications

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“…For multi-axial fatigue life prediction of complex stress states, the critical surface method based on the theory of fatigue crack initiation and propagation has good accuracy. 21,22 Therefore, the stress and strain data sets under fatigue cyclic loading without autofrettage pressure and with the best autofrettage pressure are introduced into FE-SAFE, respectively. The fatigue algorithm is defined as the Brown Miller critical surface algorithm modified by the mean stress of Morrow, the surface roughness is 0.6 < Ra < 1.6 μm, and the interaction frequency and cyclic load spectrum are defined.…”

Section: Effect Of Optimum Autofrettage Pressure On Fatigue Lifementioning

confidence: 99%

Fatigue analysis of high-pressure hydrogen storage vessel based on optimum autofrettage pressure

Shiheng

Wei-pu

et al. 2022

Journal of Reinforced Plastics and Composites

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To improve the fatigue performance of high-pressure hydrogen storage vessels, a method is proposed to determine the optimal autofrettage pressure of the vessel using numerical simulation and experimental verification. First, a finite element model considering the actual structure of the vessel is established based on grid theory. Then, the effect of autofrettage pressure on the equivalent alternating stress amplitude of liner under cyclic fatigue load is studied by using the modified equation of Smith–Watson–Topper mean stress. Lastly, the optimum autofrettage pressure is determined according to the DOT-CFFC and CGH2R standards, and the fatigue life is predicted. The results show that under the optimum autofrettage pressure, the bearing capacity of the liner under working pressure and the fatigue life under fatigue cycle load are increased by 74% and 12 times, respectively. The experimental results are in good agreement with the numerical simulation results, with an average error of 6.3%. This research has important reference significance for the preliminary design stage of composite vessels.

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Section: Effect Of Optimum Autofrettage Pressure On Fatigue Lifementioning

confidence: 99%

Fatigue analysis of high-pressure hydrogen storage vessel based on optimum autofrettage pressure

Shiheng

Wei-pu

et al. 2022

Journal of Reinforced Plastics and Composites

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show abstract

“…On the other hand, for the analysis of multiaxial fatigue life, some studies have also been carried out and various fatigue life prediction models were put forward based on equivalent stress/strain, 17–19 energy, 20–22 and critical plane approaches 23–25 . Hereinto, the equivalent stress‐, equivalent strain‐, and energy‐based models ignored the effect of mean shear stress and may lead to significant errors in the case of nonproportional loadings 26 .…”

Section: Introductionmentioning

confidence: 99%

Numerical analysis on mechanical and fatigue behaviors of aviation electrical connector considering structural effect

Luo,

Wang,

Jiang

et al. 2023

Int J Numerical Modelling

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This work is motivated by the fact that the reliability of electrical connectors influenced by their mechanical behavior and fatigue life directly affects the working performance of the whole equipment system. In this paper, theoretical analyses of insertion force, maximum stress, and fatigue life in an aviation electrical connector are presented and the corresponding mathematical models are firstly derived. Then, to numerically investigate its mechanical behavior and fatigue life, a simplified 3D FE model is developed by using ABAQUS and FE‐SAFE software and verified by experiments and theoretical analysis. Finally, the distribution and evolution characteristics of contact forces, stress and fatigue life considering the influences of reed thickness and slot width are quantitatively analyzed in details. The results indicate that the insertion force first increases and then stabilizes at the level of 0.16 N as the pin head is fully inserted into the jack, which shows an opposite to the evolution of extraction force. Moreover, the maximum value of stress and the minimum value of fatigue life are all located at the root of the jack reed. Besides, unlike the small effect of slot width, the Fimax and σmax values obviously increase and the Nf value decreases with the increment of reed thickness.

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“…[ 41–43 ] Previous studies have shown that the fatigue performance analysis method based on data‐driven method can fully reflect the influence of different IFs. [ 44–46 ] With reference to the development of data‐driven method in biology, medical, energy, and other industries, the analysis and prediction methods for fatigue performance based on data‐driven method can also be well applied in practice after further development. [ 47–51 ]…”

Section: Introductionmentioning

confidence: 99%

“…[41][42][43] Previous studies have shown that the fatigue performance analysis method based on data-driven method can fully reflect the influence of different IFs. [44][45][46] With reference to the development of data-driven method in biology, medical, energy, and other industries, the analysis and prediction methods for fatigue performance based on data-driven method can also be well applied in practice after further development. [47][48][49][50][51] The fatigue performance analysis and prediction methods based on data-driven methods can be divided into four main aspects: data acquisition, data preprocessing, data analysis, and prediction.…”

Section: Introductionmentioning

confidence: 99%

A State‐of‐Art Review on Prediction Model for Fatigue Performance of Welded Joints via Data‐Driven Method

Feng

Zhao

et al. 2023

Adv Eng Mater

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Fatigue fracture of welded joints is an important cause for engineering accidents. Due to the coexistence of so many influencing factors, the current prediction model of fatigue behavior cannot be used for all service conditions. The progress of each module (database establishment, data processing, data augmentation, dimension reduction, and comprehensive consideration of influencing factors) during the process of constructing a prediction model is summarized herein. Specifically, the state‐of‐art prediction models of fatigue strength, fatigue crack growth rate, fatigue life, and fatigue reliability are introduced. Moreover, suggestions for future work are given at the end of each section. Finally, according to the influential prediction methods, the establishment of fatigue performance prediction methods of welded joints via data‐driven method is summarized.

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A multi-axial and high-cycle fatigue life prediction model based on critical plane criterion

Cited by 11 publications

References 43 publications

Fatigue analysis of high-pressure hydrogen storage vessel based on optimum autofrettage pressure

Fatigue analysis of high-pressure hydrogen storage vessel based on optimum autofrettage pressure

Numerical analysis on mechanical and fatigue behaviors of aviation electrical connector considering structural effect

A State‐of‐Art Review on Prediction Model for Fatigue Performance of Welded Joints via Data‐Driven Method

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